Voice of the DBA

Tag: AI

  • What Can AI Really Do?

    I wonder how many of you have tried vibe coding something with an AI tool. If you haven’t, I certainly recommend it. I’ve been a bit amazed with a few of my AI Experiments, including my loading of a lot of inconsistently formatted data into a database for USD$5.

    To be clear, there’s plenty of vibe coding that might not be production-ready, but have you ever been handed code from a human developer you didn’t think was production-ready? Or deployed code like that? Certainly, AI could exacerbate the situation, but it can also spark ideas, ease (and speed) development in small ways, and tackle the backlog of things your org needs.

    Especially small tools.

    How big a concern or help will this be? I ran across an interesting article from a semi-technical person trying to build a text analysis tool. This is the type of thing we may do as database pros, but we wouldn’t have time to service every request for this assistance. There is a mixed bag of success in the piece, and a recognition that software developers have skills and knowledge that AI tools can’t necessarily duplicate in the hands of a non-pro.

    However, that’s where I think software engineers and database professionals have to learn to leverage AI tools to become more efficient, prove their worth, and, honestly, get more done without working longer hours. It’s also a place where you might guide users in producing some useful, but less mission critical software for themselves with AI. That might lower the number of requests I get.

    To me, that’s the direction I want to go with AI. More productive, less stress, and the same (or fewer) hours.

    What do you think AI can do for you? Let us know today.

    Steve Jones

    Listen to the podcast at Libsyn, Spotify, or iTunes.

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  • The Dangers of Dependencies

    Many of us working with databases know the problems of a single point of failure. We build HA/DR technologies into a lot of systems precisely because many of us know if the database goes down, a lot of stuff goes down. Broken software is easier to fix and rollback, but a broken database can be a much bigger problem.

    We also know an overloaded server doesn’t handle a workload well, hence our quest for well-written SQL code, but we often lose that battle with developers.

    In any case, as we move to a world where AI technology is used by many organizations, who often have a contract with a vendor to provide services, there is a potential issue. Imagine that you’ve setup workflows, maybe agentic loads and you depend on a company, say Anthropic, to provide those services. What if your organization gets banned?

    That happened to a company (reported on Reddit). A user got a note from Anthropic, but his entire organization got banned. That’s quite a dependency where a user in your company could cause an issue. In some sense, that’s like someone in your company sending an email that gets your organization’s email blacklisted or has Google/Microsoft/etc. cutting off access. Imagine the disruption there?

    Some of these companies providing AI services aren’t that large, and aren’t suited for the enterprise. Some of you are using vendors that might be contracting with these AI firms. Imagine your monitoring, DevOps, etc. service suddenly not working because they lost access to their AI services?

    I’d like to assume this doesn’t happen with the very large cloud vendors, but who knows. I’d like to think that not only enterprises, but even smaller companies don’t lose access because of the actions of one person. Or if they do, there’s any way way to get a response from customer service. However, I also know that Google, Amazon, and Microsoft have made it harder to get an answer from a real person.

    I didn’t talk about this recently when presenting on local AI models, but I think the future might be companies having more control over their AI tech, running them the same way we run servers in the cloud, in IaaS, with more effort required, but more controllable by the organization.

    Steve Jones

    Listen to the podcast at Libsyn, Spotify, or iTunes.

    Note, podcasts are only available for a limited time online.

  • A Cloud Dependency Failure from Amazon

    I went to sleep while reading a Kindle book on my phone. I know because my hand dropped and the phone knocked me in the forehead. I set it on the nightstand and went to sleep again.

    I woke up and was planning on reading for a few minutes before starting my Monday. When I opened the Kindle app, it asked me to log in. When I did, Amazon said my account was locked and I needed to check an email. I did, and found one from Amazon.co.uk questioning a purchase I made and asking for me to very an order number and the last 2 digits of a card to charge.

    I wasn’t sure what to do, but since my wife was complaining about her Audible account, I knew I needed to do something.

    I didn’t like the email for multiple security reasons, including not giving me a way to verify the email online. Checking Amazon’s help page said I should have a link in the email to a form. Even when I called the Amazon help line, they said I should have a link when I logged in to do so. I didn’t on either the .com or .co.uk sites, but Amazon Customer Service eventually unlocked my account.

    I wrote about Dependencies in today’s editorial, inspired by this story and the Reddit story linked in there about losing access to Claude. That’s scrary, especially in this new automated world where AI agents might be examining activity and undertake this type of action to prevent other issues. It’s an overreaching type of judgment that starts to expose the dangers of a highly interconnected world.

    I get Amazon might want to ensure my purchase was legitimate and perhaps prevent future orders, but also locking my content away (books, movies, audio, etc.) because of a shopping issue seems extreme.

    It’s certainly my issue, and I’m not sure how I untangle things for the future, but it does make me think about limiting dependencies a bit more in the future. Or at least understanding the dangers of too much on one service.

    Whether that’s the books I read or the services my company gets from any one vendor.

  • Half of All Engineers

    The AI LLM boom seems to show no sign of slowing down. Each time I think we’ve reached some level of crazy use or predictions, things take another turn. I still find myself pinging back and forth between this will be amazingly good and horrifyingly bad.

    Sometimes on the same day.

    Today, I’m a little more down on AI. I was listening to Steve Yegge on the Pragmatic Engineer podcast, and they were discussing the curve of AI usage at companies. He points out that he’s mad that Amazon let 16,000 engineers go and might let more go. He worries that companies might let 50% of their engineers go. Not necessarily because the top 50% will be more productive with AI than 100% of engineers without it. Rather the concern is that companies will get rid of half their salaries to pay for the AI tokens for the other half.

    Steve Yegge is an accomplished software engineer that has worked at Amazon and Google. Steve wrote Gastown and has been someone who not only is successful at producing code but also thinks a lot about how we produce more software.

    How coordinated and powerful are the new models? Can they really do a lot of software work that we do today? Steve thinks so, but to be fair, he’s got a lot of experience and can architect and design software well, which means he can also guide AI LLMs and agents to write more code. He also thinks the latest models, like Opus 4.6, are way more capable that most people believe.

    I also caught this post on X about a paper predicting that AI might cause economic collapse as less knowledge workers are used in various tasks. This might happen faster than we can absorb those workers who are laid off in the name of AI back into the economy in other positions. It’s a scary thought.

    The positive side of this, at least from me, is that so many organizations move slower, and so many people aren’t extremely competent software engineers, so we’ll get a lot of bad software written by non-technical people that doesn’t scale. We’ll have more database (and application) performance issues, and that will slow the use of YOLO, vibe coding.

    Plus plenty of companies just aren’t implementing or looking to pay for lots of tokens. They’ll just move slower and the world will change, but not anywhere near the pace that Steve or others think it will. We’ll see, but let me know what you think.

    For a more positive spin, I’ve been reading Reshuffle, which is a little less depressing about the future.

    Steve Jones

    Listen to the podcast at Libsyn, Spotify, or iTunes.

    Note, podcasts are only available for a limited time online.